Enroll Course: https://www.udemy.com/course/yolov8-seg/
If you’re looking to dive into the world of computer vision and enhance your skills in object detection and segmentation, the course ‘YOLOv8實例分割實戰：訓練自己的資料集’ on Coursera is an excellent choice. This practical course introduces learners to YOLOv8, an advanced version of the popular YOLO (You Only Look Once) object detection model, which now supports tasks like target detection, tracking, instance segmentation, image classification, and pose estimation. The course is designed to be highly hands-on, guiding students through the entire process of annotating their datasets using LabelMe, preparing data, modifying configuration files, and training custom models.
One of the standout features of this course is its focus on real-world scenarios, specifically automotive driving scenes. You’ll learn how to annotate images of road scenes, including potholes, vehicles, and lane lines, and then train a model to perform multi-object instance segmentation. Whether you’re a beginner or an experienced practitioner, the course provides practical demonstrations on both Windows and Ubuntu, covering software installation, environment setup, and performance evaluation.
I highly recommend this course for anyone interested in autonomous driving, robotics, or general computer vision development. The step-by-step instructions, combined with practical project work, make complex concepts accessible and applicable. By the end of this course, you’ll have the skills to train your own YOLOv8 models tailored to your specific needs, making it a valuable investment for your AI toolkit.
Enroll Course: https://www.udemy.com/course/yolov8-seg/